Rinku Diwakar
Builder working across software engineering, applied AI, and hardware-software systems. Founder of Pradrix.
Dr. B. R. Ambedkar National Institute of Technology (NIT) Jalandhar
Bachelor of Technology (B.Tech) in Electrical Engineering
Python, C++, SQL, JavaScript, TypeScript, FastAPI, Flask, REST APIs, Celery, Redis, React.js
PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas, NumPy, RAG, Agentic AI, LangChain, Hugging Face, Vector DBs
AWS (EC2, S3), Docker, Kubernetes, Amazon EKS, GitHub Actions CI/CD, MLflow, DVC
PostgreSQL, MySQL, MongoDB, Supabase, Raspberry Pi, Arduino C++, Linux, Git, Postman
Kavach
completedAI-powered voice authentication and physical smart access system.
People frequently forget physical keys, while traditional contact biometrics require physical touch and specialized optical sensors. We asked: What if human voice could securely become the key?
NanoTrade
completedReal-time paper trading platform with custom matching engine.
Most trading demos are simple database dashboards that fail to simulate realistic order-book mechanics, execution latency, queue matching, and portfolio state reconciliation.
SkillGap AI
completedSemantic embedding and RAG engine for resume and job description fit analysis.
A résumé and a job description can superficially look like a match while still concealing critical capability gaps, leading to poor hiring signals and unfocused career preparation.
MovieSentiment
completedProduction-oriented ML discovery platform with automated MLOps & EKS deployment.
Machine learning models often remain trapped in Jupyter notebooks without robust CI/CD, containerized packaging, automated retraining, and scalable Kubernetes orchestration.
Bike Demand Prediction ML System
completedProduction ML demand forecasting application developed at TS Bridge.
Urban mobility fleets experience extreme utilization volatility due to weather, seasonal shifts, and commuting patterns, requiring precise predictive demand modeling to prevent asset shortages.
Large-Scale Data Preprocessing & EDA
completedData wrangling and feature engineering pipeline on 50,000+ records at CourseVita.
Raw real-world datasets arrive laden with missing values, inconsistent encodings, extreme outliers, and duplicate records that degrade downstream modeling.
Vehicle Insurance ML Pipeline
completedEnd-to-end predictive classification pipeline with modular MLOps architecture.
Assessing vehicle insurance claim propensities requires handling severe class imbalances, multi-modal features, and repeatable retraining pipelines.
Industrial Sensor Fault Detection
completedAnomaly detection system for industrial sensor telemetries.
Industrial machinery sensor drifts and electrical spikes often go undetected until catastrophic mechanical failure occurs.